Risk identification in supply chain

1. A computer-implemented method for controlling operations of physical sites based on modeling of a supply chain network including the physical sites, the method comprising: creating, storing in memory, and continuously monitoring and updating a visual model of a supply chain network, the created visual model including: (i) one or more logical stations graphically representing physical sites in the supply chain network, the physical sites including a manufacturing site, and (ii) one or more logical transits graphically representing transportation of materials between the represented physical sites; for each given logical station that graphically represents a physical site, using a processor and implementing: automatically identifying risk values in real time for each risk category in a set of risk categories associated with the given logical station, the risk categories including at least a risk associated with materials and a risk associated with resource usage and flow between physical areas internal to a modeled manufacturing site, the identifying determining the risk values based on physical conditions related to: (a) the physical site represented by the given logical station, (b) each physical site, of a plurality of physical sites, represented by a respective logical station positioned in a downstream supply chain path to the given logical station, and (c) each transportation represented by a respective logical transit positioned in the downstream supply chain path, generating a graphical representation visually comparing the identified risk values for each risk category in the set of risk categories of the given logical station, the graphical representation being displayed at the given logical station in the visual model, automatically determining a total risk value for the given logical station based on the identified risk values for each risk category in the set of risk categories, wherein the determining designates a visual indication of the determined total risk value based on comparing the determined total risk value to a set of tolerance ranges that specify probabilistic distance of the determined total risk value from a risk tolerance threshold, the designated visual indication being presented at the given logical station in the visual model; displaying in a computer screen view, the visual model having the generated graphical representations at respective logical stations and having the designated visual indications at respective logical stations, said displayed visual model providing risk assessment in the modeled supply chain network; automatically updating the visual model to minimize associated risk in the modeled supply chain network; and outputting a signal to automatically control operations of the physical sites by automatically programming control systems for the physical sites, automatically programming the transportation modeled in the supply chain network, or automatically programming other modeling systems that control operation of the physical sites or the transportation of materials between the physical sites.

2. The method of claim 1 , wherein the set of risk categories further includes at least one of: environmental risk, source risk, delivery risk, planning risk, and production risk.

3. The method of claim 2 , wherein the identified risk values for the environmental risk, source risk, delivery risk, and planning risk categories include risk based on geolocation of the represented physical site.

4. The method of claim 2 , wherein the identified risk value for the delivery risk category is based on methods for the transportation of materials between the represented physical sites.

5. The method of claim 2 , wherein the identified risk value for the production risk category is based on production processes at the represented physical site.

6. The method of claim 1 , wherein the designated visual indication displays a color including at least one of: red, green, and yellow, the color displayed based on the comparison between the determined total risk value and the set of tolerance ranges risk tolerance threshold.

7. The method of claim 1 , wherein the one or more logical stations represent at least one of: a supplier site, a production site, an inventory site, a distribution site, a storage site, a retailer site, and a customer site.

8. The method of claim 1 , wherein the identified risk values and the determined total risk value are probabilistically calculated by the processor using a fault tree analysis.

9. The method of claim 1 further comprising: based on the identified risk values for a given logical station, determining probabilistic risk contributed by each downstream supply chain path for the given logical station; and visually indicating the determined probabilistic risk at the respective supply chain path in the displayed visual model.

10. The method of claim 9 further comprising: determining a critical supply chain path that contributes a highest probabilistic risk to the given logical station; and visually indicating the respective highest probabilistic risk at the respective supply chain path in the visual model.

11. A computer system for controlling operations of physical sites based on modeling of a supply chain network including the physical sites, the computer system comprising: a user interface configured to display a visual model of a supply chain network, the visual model including: (i) one or more logical stations graphically representing physical sites in the supply chain network, the physical sites including a manufacturing site, and (ii) one or more logical transits graphically representing transportation of materials between the represented physical sites; at least one processor communicatively coupled to the user interface and to associated computer memory, the at least one processor configured to: create, maintain in the computer memory, and continuously monitor and update the visual model of the supply chain network for display on the user interface; for each given logical station of the one or more logical stations that graphically represent physical sites, the at least one processor configured to: in an automated manner identify risk values in real time for each risk category in a set of risk categories associated with the given logical station, the risk categories including at least a risk associated with materials and a risk associated with resource usage and flow between physical areas internal to a modeled manufacturing site, the identifying determining the risk values based on physical conditions related to: (a) the physical site represented by the given logical station, (b) each physical site, of a plurality of physical sites, represented by a respective logical station positioned in a downstream supply chain path to the given logical station, and (c) each transportation represented by a respective logical transit positioned in the downstream supply chain path, generate a graphical representation visually comparing the identified risk values for each risk category in the set of risk categories of the given logical station, the graphical representation being displayed at the given logical station in the visual model, automatically determine a total risk value for the given logical station based on the identified risk values for each risk category in the set of risk categories, wherein the determining designates a visual indication of the determined total risk value based on comparing the determined total risk value to a set of tolerance ranges that specify probabilistic distance of the determined total risk value from a risk tolerance threshold, the designated visual indication being presented at the given logical station in the visual model; display on the user interface, the visual model having the generated graphical representations at respective logical stations and having the designated visual indications at respective logical stations, said displayed visual model providing risk assessment in the modeled supply chain network; automatically update the visual model to minimize associated risk in the modeled supply chain network; and output a signal to automatically control operations of the physical sites by automatically programming control systems for the physical sites, automatically programming the transportation modeled in the supply chain network, or automatically programming other modeling systems that control operation of the physical sites or the transportation of materials between the physical sites.

12. The computer system of claim 11 , wherein the set of risk categories further includes at least one of: environmental risk, source risk, delivery risk, planning risk, and production risk.

13. The computer system of claim 12 , wherein the identified risk values for the environmental risk, source risk, delivery risk, and planning risk categories include risk based on geolocation of the represented physical site.

14. The computer system of claim 12 , wherein the identified risk value for the delivery risk category is based on methods for the transportation of materials between the represented physical sites.

15. The computer system of claim 12 , wherein the identified risk value for the production risk category is based on production processes at the represented physical site.

16. The computer system of claim 11 , wherein the designated visual indication displays a color including at least one of: red, green, and yellow, the color displayed based on the comparison between the determined total risk value and the set of tolerance ranges.

17. The computer system of claim 11 , wherein the one or more logical stations represent at least one of: a supplier site, a production site, an inventory site, a distribution site, a retailer site, and a customer site.

18. The computer system of claim 11 , wherein the identified risk values and the determined total risk value are probabilistically calculated by the processor using a fault tree analysis.

19. The computer system of claim 11 , wherein the at least one processor is further configured to: based on the identified risk values for a given logical station, determine probabilistic risk contributed by each downstream supply chain path for the given logical station; visually indicate the determined probabilistic risk at the respective supply chain path in the visual model on the user interface; determine a critical supply chain path that contributes a highest probabilistic risk to the given logical station; and visually indicate the respective highest probabilistic risk at the respective supply chain path in the displayed visual model on the user interface.

20. A computer program product comprising a non-transitory computer-readable medium storing instructions for controlling operations of physical sites based on modeling of a supply chain network including the physical sites, the instructions, when loaded and executed by a processor, cause the processor to: create, store in computer memory, and continuously monitor and update a visual model of a supply chain network, the created visual model including: (i) one or more logical stations graphically representing physical sites in the supply chain network, the physical sites including a manufacturing site, and (ii) one or more logical transits graphically representing transportation of materials between the represented physical sites; for each given logical station of the one or more logical stations that graphically represent physical sites, using a processor configured to: automatically identify risk values in real time for each risk category in a set of risk categories associated with the given logical station, the risk categories including at least a risk associated with materials and a risk associated with resource usage and flow between physical areas internal to a modeled manufacturing site, wherein the identifying is based on physical conditions related to: (a) the physical site represented by the given logical station, (b) each physical site, of a plurality of physical sites, represented by a respective logical station positioned in a downstream supply chain path to the given logical station, and (c) each transportation represented by a respective logical transit positioned in the downstream supply chain path, generate a graphical representation visually comparing the identified risk values for each risk category in the set of risk categories of the given logical station, the graphical representation being displayed at the given logical station in the visual model, automatically determine a total risk value for the given logical station based on the identified risk values for each risk category in the set of risk categories, wherein the determining designates a visual indication of the determined total risk value based on comparing the determined total risk value to a set of tolerance ranges that specify probabilistic distance of the determined total risk values from a risk tolerance threshold, the designated visual indication being presented at the given logical station in the visual model; display the visual model having the generated graphical representations at respective logical stations and having the designated visual indications at respective logical stations, said displayed visual model providing risk assessment in the modeled supply chain network; automatically update the visual model to minimize associate risk in the modeled supply chain network; and output a signal to automatically control operations of the physical sites by automatically programming control systems for the physical sites, automatically programming the transportation modeled in the supply chain network, or automatically programming other modeling systems that control operation of the physical sites or the transportation of materials between the physical sites.